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National Chung Hsing University Institutional Repository - NCHUIR > 農業暨自然資源學院 > 農藝學系 > 依資料類型分類 > 期刊論文 >  Forecasting agricultural output with an improved grey forecasting model based on the genetic algorithm

Please use this identifier to cite or link to this item: http://nchuir.lib.nchu.edu.tw/handle/309270000/145753

標題: Forecasting agricultural output with an improved grey forecasting model based on the genetic algorithm
作者: Ou, Shang-Ling
Contributors: Wei Chun Wang
關鍵字: Agricultural output;Forecasting;GM(1,1);Background value;Genetic algorithm
日期: 2012
Issue Date: 2013-07-02 10:22:53 (UTC+8)
摘要: Agriculture is the foundation of the national economy. Thus, an appropriate tool for forecasting agricultural
output is very important for policy making. In this study, both modified background value calculation
and use of a genetic algorithm to find the optimal parameters were adopted simultaneously to
construct an improved GM(1,1) model (GAIGM(1,1)). The sample period of the forecasting models
includes the annual values for the data of Taiwan’s agricultural output from 1998 to 2010. The mean
absolute percentage error and the root mean square percentage error are two criteria with which to compare
the various forecasting models results. Both in-sample and out-of-sample forecast performance
results show that the GAIGM(1,1) model has highly accurate forecasting. Therefore, the GAIGM(1,1)
model can raise the forecast accuracy of the GM(1,1) model, and it is suitable for use in modeling and
forecasting of agricultural output.
Relation: Computers and Electronics in Agriculture, Volume 85, Page(s) 33–39.
Appears in Collections:[依資料類型分類] 期刊論文

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